Security Incident Classification Applied to Automated Decisions Using Machine Learning

Eduardo Eloy Loza Pacheco; Mayra Lorena Díaz Sosa; Christian Carlos Delgado Elizondo; Miguel Jesús Torres Ruiz; Dulce Lourdes Loza Pacheco

doi:10.1007/978-3-030-89586-0_3

Security Incident Classification Applied to Automated Decisions Using Machine Learning

Eduardo Eloy Loza Pacheco, Mayra Lorena Díaz Sosa, Christian Carlos Delgado Elizondo, Miguel Jesús Torres Ruiz, Dulce Lourdes Loza Pacheco

Centro de Investigación en Computación (CIC)

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

There is an immense number of attacks on the logical infrastructure of an organization. Cybersecurity professionals need tools to help discriminate levels of attacks to design operational plans to prevent, mitigate, and restore without significant damage to an organization’s resources. Machine learning helps build valuable models to identify relevant values of a vulnerability vector attack needed to improve our security plan. The following work presents a framework that uses a machine learning model that classifies the level of an incident detection indicator.

Idioma original	Inglés
Título de la publicación alojada	Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings
Editores	Miguel Félix Mata-Rivera, Roberto Zagal-Flores
Editorial	Springer Science and Business Media Deutschland GmbH
Páginas	23-34
Número de páginas	12
ISBN (versión impresa)	9783030895853
DOI	https://doi.org/10.1007/978-3-030-89586-0_3
Estado	Publicada - 2021
Evento	10th International Congress on Telematics and Computing, WITCOM 2021 - Virtual, Online Duración: 8 nov. 2021 → 12 nov. 2021

Serie de la publicación

Nombre	Communications in Computer and Information Science
Volumen	1430 CCIS
ISSN (versión impresa)	1865-0929
ISSN (versión digital)	1865-0937

Conferencia

Conferencia	10th International Congress on Telematics and Computing, WITCOM 2021
Ciudad	Virtual, Online
Período	8/11/21 → 12/11/21

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10.1007/978-3-030-89586-0_3

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Loza Pacheco, E. E., Díaz Sosa, M. L., Delgado Elizondo, C. C., Torres Ruiz, M. J., & Loza Pacheco, D. L. (2021). Security Incident Classification Applied to Automated Decisions Using Machine Learning. En M. F. Mata-Rivera, & R. Zagal-Flores (Eds.), Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings (pp. 23-34). (Communications in Computer and Information Science; Vol. 1430 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-89586-0_3

Loza Pacheco, Eduardo Eloy ; Díaz Sosa, Mayra Lorena ; Delgado Elizondo, Christian Carlos et al. / Security Incident Classification Applied to Automated Decisions Using Machine Learning. Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings. editor / Miguel Félix Mata-Rivera ; Roberto Zagal-Flores. Springer Science and Business Media Deutschland GmbH, 2021. pp. 23-34 (Communications in Computer and Information Science).

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title = "Security Incident Classification Applied to Automated Decisions Using Machine Learning",

abstract = "There is an immense number of attacks on the logical infrastructure of an organization. Cybersecurity professionals need tools to help discriminate levels of attacks to design operational plans to prevent, mitigate, and restore without significant damage to an organization{\textquoteright}s resources. Machine learning helps build valuable models to identify relevant values of a vulnerability vector attack needed to improve our security plan. The following work presents a framework that uses a machine learning model that classifies the level of an incident detection indicator.",

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Loza Pacheco, EE, Díaz Sosa, ML, Delgado Elizondo, CC, Torres Ruiz, MJ & Loza Pacheco, DL 2021, Security Incident Classification Applied to Automated Decisions Using Machine Learning. En MF Mata-Rivera & R Zagal-Flores (eds.), Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings. Communications in Computer and Information Science, vol. 1430 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 23-34, 10th International Congress on Telematics and Computing, WITCOM 2021, Virtual, Online, 8/11/21. https://doi.org/10.1007/978-3-030-89586-0_3

Security Incident Classification Applied to Automated Decisions Using Machine Learning. / Loza Pacheco, Eduardo Eloy; Díaz Sosa, Mayra Lorena; Delgado Elizondo, Christian Carlos et al.
Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings. ed. / Miguel Félix Mata-Rivera; Roberto Zagal-Flores. Springer Science and Business Media Deutschland GmbH, 2021. p. 23-34 (Communications in Computer and Information Science; Vol. 1430 CCIS).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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Loza Pacheco EE, Díaz Sosa ML, Delgado Elizondo CC, Torres Ruiz MJ, Loza Pacheco DL. Security Incident Classification Applied to Automated Decisions Using Machine Learning. En Mata-Rivera MF, Zagal-Flores R, editores, Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 23-34. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-89586-0_3

Security Incident Classification Applied to Automated Decisions Using Machine Learning

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